Motion-compensated inverse filtering with band-pass filters for motion blur reduction

ABSTRACT

This invention relates to a method, a computer program, a computer program product, and a device for reducing motion blur of images of a video signal shown on a hold-type display ( 101 ), comprising estimating ( 1102 ) motion vectors of moving components in said images of said video signal; band-pass filtering ( 1100, 1101 ) said video signal with respect to a spatial frequency domain, wherein said band-pass filtering at least partially depends on said estimated motion vectors, and wherein with increasing length of said estimated motion vectors, the passband of said band-pass filtering adaptively shifts from high spatial frequencies to medium spatial frequencies; and combining ( 1104 ) said video signal and said band-pass filtered video signal to produce an input video signal for said hold-type display.

FIELD OF THE INVENTION

This invention relates to a method for reducing motion blur of images ofa video signal shown on a hold-type display.

BACKGROUND OF THE INVENTION

Over the last years, the traditional cathode ray tube (CRT) display hashad to face increasing competition from alternative display principles,which are mainly based on active-matrix technology. In particular,active-matrix liquid crystal displays (AM-LCDs) have increased inperformance and decreased in price so dramatically, that the marketshare of the CRT is decreasing at a rapid pace. The main differentiatingfeature of these new display principles is their size: LCDs are thin,flat and lightweight. This has enabled the first market for thesedisplays: laptop computers. By now, the LCD has also almost taken overthe desktop monitor market, where not only its size has made thedifference, but also its uniform, sharp, and flicker-free picturereproduction. Nowadays, the CRT is also having to face competition fromthe LCD in its last stronghold: television.

To make a good television display, the LCD has had to overcome previousdrawbacks, for example a limited viewing angle and color performance.However, the CRT is still unbeaten in one major aspect: motionportrayal. In that area, LCDs perform much worse, since the LC-moleculesthat provide the basic display effect react slowly to image changes.This causes an annoying smearing (blurring) of moving objects, whichmakes the LCD unsuited for video applications. Therefore, a lot ofeffort has been put into speeding up the response of LC materials. Thiscan be done by applying better materials, or by improved LC cell design.There is also a well known method for response time improvement based onvideo processing, called ‘overdrive’. Overdrive improves the responsespeed of the LC pixels by changing the drive values depending on theapplied gray level transition. This enables a reduction of the responsetime to within the frame period. Currently, the best displays availablelist response times below the frame period (17 ms at 60 Hz). This is acrucial value, since the worst blurring artifacts are prevented for anLCD that can respond to image changes within the frame period.

However, speeding up the response of LC materials to lower values is notenough to completely avoid motion blur. This is caused by the activematrix principle itself, which exhibits a sample-and-holdcharacteristic, causing light emission during the whole frame time(hold-type display). This is a major difference with the very short(microsecond) light flashes produced by the phosphors of the CRT(impulse-type display). It is well known that this prolonged lightemission does not match very well with the way humans perceive movingimages. As will be further explained in the next sections, the human eyewill track moving objects on the screen, thereby imaging the light,belonging to each fixed point in a frame, onto a series of points on theretina. This ‘point spreading’ results in a loss of sharpness of movingobjects.

The basic function of a display system is to reconstruct the physicallight emissions, corresponding to the original image, at the correctposition and time on the screen from the received space-time discretevideo signal. The characteristics of this reconstruction process,especially when combined with characteristics of the human visualsystem, can explain many image quality artifacts that occur in practicaldisplay systems.

The very basic representation of the signal chain 1 from original todisplayed image is shown in FIG. 1. The original scene, represented as atime varying image, is a space-time-continuous intensity functionI_(c)({right arrow over (x)},t), where {right arrow over (x)} has twodimensions: {right arrow over (x)}=(x,y)^(T). This original image issampled by the camera 100 in time and space. Since the spatial samplingis outside the scope of this specification, we will refer to it onlyoccasionally from now on. The temporal behavior, however, will be themain focus for the remainder of this specification. The sampling processis described by:I _(s)({right arrow over (x)},t)=I _(c)({right arrow over(x)},t)·Λ({right arrow over (x)},t),  (1)

where Λ({right arrow over (x)},t) is a three-dimensional lattice ofδ-impulses. We can assume a rectangular sampling lattice, which isdescribed by sampling intervals Δ{right arrow over (x)}=(Δx,Δy) and Δt:

$\begin{matrix}{{\Lambda\left( {\overset{\rightarrow}{x},t} \right)} = {\sum\limits_{k,l,m}{{\delta\left( {x - {{k \cdot \Delta}\; x}} \right)} \cdot {\delta\left( {y - {{l \cdot \Delta}\; y}} \right)} \cdot {{\delta\left( {t - {{m \cdot \Delta}\; t}} \right)}.}}}} & (2)\end{matrix}$

The reconstruction of the physical light emission by the display 101 canbe described by a convolution with the display aperture (also known asreconstruction function or point spread function). This aperture is alsoa function of space and time: A({right arrow over (x)},t). The image, asproduced by the display 101, becomes:

$\begin{matrix}\begin{matrix}{{I_{d}\left( {\overset{\rightarrow}{x},t} \right)} = {{I_{s}\left( {\overset{\rightarrow}{x},t} \right)}*{A\left( {\overset{\rightarrow}{x},t} \right)}}} \\{= {\left( {{I_{c}\left( {\overset{\rightarrow}{x},t} \right)} \cdot {\Lambda\left( {\overset{\rightarrow}{x},t} \right)}} \right)*{A\left( {\overset{\rightarrow}{x},t} \right)}}}\end{matrix} & (3)\end{matrix}$

The two operations of sampling and reconstruction account for a numberof characteristic differences between the displayed image and theoriginal image. These are best described by a frequency domaindescription, so we apply the Fourier transform F(F({right arrow over(x)},t))=F^(f)({right arrow over (f)}_(x),f_(t)) to Eq. (3):I _(d) ^(f)({right arrow over (f)} _(x) ,f _(t))=(I _(c) ^(f)({rightarrow over (f)} _(x) ,f _(t))*Λ^(f)({right arrow over (f)} _(x) ,f_(t)))·A ^(f)({right arrow over (f)} _(x) ,f _(t)),  (4)

where the Fourier transform Λ^(f)({right arrow over (f)}_(x),f_(t)) oflattice Λ({right arrow over (x)},t) is the reciprocal lattice, withspacings (Δx)⁻¹, (Δy)⁻¹ and (Δt)⁻¹ (the frame rate).

The spatio-temporal spectrum of the original image, the sampled image,the displayed image and the finally perceived image as a function of thenormalized temporal frequency f_(t)Δt and the normalized spatialfrequency f_(x)Δx are depicted in the four plots of FIG. 2,respectively, for the case of an impulse-type (CRT) display. To simplifythe illustration, we omit the spatial repeats, as if the signal wascontinuous in the spatial dimension. For the displayed images, this isequivalent to assuming that the spatial dimension has been reconstructedperfectly, i.e. the original continuous signal was spatiallyband-limited according to the Nyquist criterion, and the reconstructioneffectively eliminates the repeat spectra.

In the temporal dimension, the impulse nature of the light emissiongives a flat reconstruction spectrum. As a consequence of this flatspectrum, the temporal frequencies in the baseband f_(t)<(2Δt)⁻¹ are notattenuated, but also at least the lowest order repeats are passed.

The image, as it is finally perceived by the viewer, is also determinedby the characteristics of the human visual system (HVS). In the temporaldomain, the HVS mainly behaves as a low-pass filter, since it isinsensitive to higher frequencies. The fourth plot of FIG. 2 shows thatthe perceived image is identical to the original image (cf. first plotof FIG. 2), if we assume that the eye's low-pass eliminates all repeatspectra. This assumption is not always true, which leads to one of themost widely known artifacts in display systems: large area flicker. Thisis caused by the first repeat spectrum (at low spatial frequencies) thatis not completely suppressed for frame rates approximately smaller than75 Hz.

Active-matrix displays like LCDs do not have an impulse-type lightemission. The fastest displays that are currently available haveresponse times shorter than the frame period. However, even these willstill have a light emission during the whole frame period due to thesample-and-hold behavior of the active matrix and the continuousillumination by the backlight. This behavior results in a temporal “box”reconstruction function with a width equal to the hold time T_(h). Inthe frequency domain, this becomes a sinc characteristic:A ^(f)({right arrow over (f)} _(x) ,f _(t))=sin c(πf _(t) T _(h))  (5)

The spectrum of the sampled image, of the aperture A({right arrow over(x)},t), of the displayed image and of the finally perceived image forsuch a hold-type display are depicted in the four plots of FIG. 3,respectively. This immediately shows a distinctive advantage ofhold-type displays over impulse-type displays: the sinc characteristicsuppresses the repeat spectra in the displayed image (cf. the third plotof FIG. 3), and even has zero transmission at the sampling frequency.This eliminates large area flicker at all frame rates.

It may seem that the sample-and-hold behavior of the hold-type displaysresults in a better display than an impulse-type light emission. Forstatic images this is indeed the case. However, the conclusion changesfor a moving image:I _(m)({right arrow over (x)},t)=I _(c)({right arrow over (x)}+{rightarrow over (v)}t,t),  (6)

where {right arrow over (v)} is the speed of the moving image over thescreen, measured here in the same units that are used for {right arrowover (x)} and t. When the sampling intervals Δ{right arrow over(x)}=(Δx,Δy) are known, {right arrow over (v)} can also be expressed in“pixels per frame”. This corresponds to the “motion vector” or “framedisplacement vector”.

Eq. (6) can also be transformed to the frequency domain, where itbecomes:I _(m) ^(f)({right arrow over (f)} _(x) ,f _(t))=I _(c) ^(f)({rightarrow over (f)} _(x) ,f _(t) −{right arrow over (v)}·{right arrow over(f)} _(x)).  (7)

This movement results in a shearing of the spectrum as shown in thesecond plot of FIG. 4, in comparison to the spectrum of the stilloriginal image in the first plot of FIG. 4. The shearing of the spectrumreflects that spatial variations in a moving object will generatetemporal variations.

This moving image is then sampled (cf. the third plot of FIG. 4) andreconstructed in the display chain, after which it reaches the eye. Theperception of moving images is characterized by another importantproperty of the HVS: the eye tracking. The viewer tries to follow movingobjects across the screen in order to produce a static image on theretina. This mechanism is well studied, and enables the HVS to perceivemoving images with a high level of detail. The image on the retina of aneye tracking viewer is described by the inverse of the relations in Eqs.(6) and (7):I _(e)({right arrow over (x)},t)=I _(d)({right arrow over (x)}−{rightarrow over (v)}t,t)I _(e) ^(f)({right arrow over (f)} _(x) ,f _(t))=I _(d) ^(f)({rightarrow over (f)} _(x) ,f _(t) +{right arrow over (v)}·{right arrow over(f)} _(x))  (8)

The whole chain 5 from original image to perceived image, comprising amotion instance 500 (due to moving objects), a sampling instance 501(e.g. a camera), a reconstruction instance 502 (e.g. a display), atracking instance 503 (the viewer tracking the motion) and a low-passfilter 504 (the eye), is shown in FIG. 5. Substituting Eq. (3) in Eq.(8) and applying Eq. (7), gives the image as projected onto the retinaof the eye tracking viewer:

$\begin{matrix}\begin{matrix}{{I_{e}^{f}\left( {{\overset{\rightarrow}{f}}_{x},f_{t}} \right)} = {\left( {{I_{m}^{f}\left( {{\overset{\rightarrow}{f}}_{x},f_{t},{{+ \overset{\rightarrow}{v}} \cdot {\overset{\rightarrow}{f}}_{x}}} \right)}*{\Lambda^{f}\left( {{\overset{\rightarrow}{f}}_{x},{f_{t} + {\overset{\rightarrow}{v} \cdot {\overset{\rightarrow}{f}}_{x}}}} \right)}} \right) \cdot {A^{f}\left( {{\overset{\rightarrow}{f}}_{x},{f_{t} + {\overset{\rightarrow}{v} \cdot {\overset{\rightarrow}{f}}_{x}}}} \right)}}} \\{= {\left( {{I_{c}^{f}\left( {{\overset{\rightarrow}{f}}_{x},f_{t}} \right)}*{\Lambda^{f}\left( {{\overset{\rightarrow}{f}}_{x},f_{t},{{+ \overset{\rightarrow}{v}} \cdot {\overset{\rightarrow}{f}}_{x}}} \right)}} \right) \cdot {A^{f}\left( {{\overset{\rightarrow}{f}}_{x},{f_{t} + {\overset{\rightarrow}{v} \cdot {\overset{\rightarrow}{f}}_{x}}}} \right)}}}\end{matrix} & \left. (9) \right)\end{matrix}$

The perceived image I_(p) ^(f)({right arrow over (f)}_(x),f_(t)) afterlow-pass filtering by the eye is shown in the third plot of FIG. 6 foran impulse-type display, and in the fourth plot of FIG. 7 for ahold-type display, wherein the plots of FIGS. 6 and 7 complement theplots of FIG. 4, respectively. The image after the eye low-pass isobtained by only looking at the frequencies f_(t)≈0, again assumingperfect reconstruction in the spatial domain. There we can see that theeffect of the temporal aperture function of the display, combined witheye tracking, can be described as spatial filtering of moving images:

$\begin{matrix}\begin{matrix}{{I_{p}^{f}\left( {\overset{\rightarrow}{f}}_{x} \right)} = {{I_{c}^{f}\left( {\overset{\rightarrow}{f}}_{x} \right)} \cdot {A^{f}\left( {{\overset{\rightarrow}{f}}_{x},{\overset{\rightarrow}{v} \cdot {\overset{\rightarrow}{f}}_{x}}} \right)}}} \\{= {{I_{c}^{f}\left( {\overset{\rightarrow}{f}}_{x} \right)} \cdot {H^{f}\left( {\overset{\rightarrow}{f}}_{x} \right)}}}\end{matrix} & (10)\end{matrix}$

with the spatial low-pass filterH ^(f)({right arrow over (f)} _(x))=sin c(π{right arrow over (v)}·{rightarrow over (f)} _(x) T _(h)).  (11)

The filter H^(f)({right arrow over (f)}_(x)) of Eq. (11) depends on thespeed of motion {right arrow over (v)} and the hold time (frame period)T_(h).

FIG. 8 schematically depicts the amplitude response of this filter as afunction of motion (speed) |{right arrow over (v)}| (in pixels perframe) and normalized spatial frequency f_(x)Δx along the motiondirection

${{\overset{\rightarrow}{f}}_{x} \cdot \frac{\overset{\rightarrow}{v}}{\overset{\rightarrow}{v}}},$wherein the white region represents amplitudes between 1 and 0.5 (lowattenuation) and wherein the shaded region represents amplitudes between0.4 and 0 (high attenuation).

Although the temporal “hold” aperture is beneficial with respect tolarge area flicker, it will cause a spatial blurring of moving objectson the retina of the viewer. Higher spatial frequencies will beattenuated by the sinc characteristic, and the spatial frequency fromwhich the attenuation starts will get smaller with increase with speed,thus affecting an extended spatial frequency region. Furthermore, thisblurring will only occur along the motion direction. The sharpnessperpendicular to the motion of each object is not affected.

Eq. (11) suggests that, in order to decrease this effect, the hold timeT_(h) must be decreased. This can be achieved in two ways. First of all,the frame rate can be increased. In order to have the required effect,this must be done with a motion-compensated frame rate conversion, sincea simple frame repetition will result in the same effective hold time.Secondly, without changing the frame rate, we can decrease the period(or better: duty-cycle) of light emission. For LCDs, this can berealized by switching the backlight on only during a part of the frametime, using a so-called “scanning backlight”.

A third option for decreasing motion blur due to the sample-and-holdeffect, based on Eq. (11), is to use only video processing, and does notrequire modification of display or backlight. The low pass filtering ofthe display+eye combination 903 (consisting of reconstruction 901 by thedisplay and tracking/low-pass filtering 902 by the viewer/eye) ispre-compensated in the video domain, as shown in the display chain 9 ofFIG. 9. This can be achieved by using the inverse filter 900 of thefilter H^(f)({right arrow over (f)}_(x)) of Eq. (11):

$\begin{matrix}{{F_{inv}^{f}\left( {\overset{\rightarrow}{f}}_{x} \right)} = \frac{1}{{sinc}\left( {\pi\overset{\rightarrow}{v}\;{\overset{\rightarrow}{f}}_{x}T_{h}} \right)}} & (12)\end{matrix}$

The inverse filter H_(inv) ^(f)({right arrow over (f)}_(x)) is a purelyspatial filter, reflecting the observation that the temporal aperture ofthe display, combined with eye tracking, results in a spatial low-passfilter H^(f)({right arrow over (f)}_(x)). The cascade 9 of the inversefilter 900 and the display+eye combination 903 further along the chainshould result in a perceived image that approaches the original image aswell as possible.

EP 0 657 860 A2 discloses the use of an approximation {tilde over(H)}_(inv) ^(f)({right arrow over (f)}_(x)) of such a pre-compensationfilter H_(inv) ^(f)({right arrow over (f)}_(x)) 900 in the shape of aspeed-dependent high spatial frequency enhancement filter (or highspatial frequency boosting filter), which enhances the spectrum of thevideo signal at high spatial frequencies according to the speed of themoving components, wherein said spectrum at high spatial frequencies isrelated to moving components in the images of the video signal. Therein,the cut-off frequency of the spatial frequency enhancement filter (fromwhich on the enhancement starts) is adjusted according to motion vectorsthat are estimated by a motion vector estimator. The spatial frequencyenhancement filter {tilde over (H)}_(inv) ^(f)({right arrow over(f)}_(x)) deployed in EP 0 657 860 A2 is not the exact inverse filterH_(inv) ^(f)({right arrow over (f)}_(x)) as defined in Eq. (12), becausethe restoration of those frequencies which have been attenuated to verylow levels (for instance in the zeroes of the spatial low pass filterH^(f)({right arrow over (f)}_(x)) of Eq. (11)), e.g. below noisethresholds, can not realistically be achieved.

FIG. 10 depicts the transfer function of the spatial low-pass filterH^(f)({right arrow over (f)}_(x)) 1000 of Eq. (11), of the inversefilter H_(inv) ^(f)({right arrow over (f)}_(x)) 1001 of Eq. (12), and ofan approximation 1002 of the inverse filter H_(inv) ^(f)({right arrowover (f)}_(x)) of Eq. (12) as a function of the spatial frequency,wherein said approximation 1002 is similar to the high spatial frequencyenhancement filter of EP 0 657 860 A2.

Spatial frequency enhancement filters as disclosed in EP 0 657 860 A2also enhance the high spatial frequency components of noise that ispresent in the sampled images of the video signal. However, in flat(undetailed) image parts, the motion estimator has a high probability ofestimating the wrong motion vector that determines the cut-off frequencyof the spatial frequency enhancement filter, resulting in undesirablenoise amplification at high spatial frequency enhancement filter gains,which significantly degrade the quality of the images of the videosignal.

SUMMARY OF THE INVENTION

In view of the above-mentioned problem, it is, inter alia, an object ofthe present invention to provide improved methods, computer programs,computer program products and devices for reducing motion blur of imagesof a video signal shown on a hold-type display.

A method is proposed for reducing motion blur of images of a videosignal shown on a hold-type display, comprising estimating motionvectors of moving components in said images of said video signal;band-pass filtering said video signal with respect to a spatialfrequency domain, wherein said band-pass filtering at least partiallydepends on said estimated motion vectors, and wherein with increasinglength of said estimated motion vectors, the pass-band of said band-passfiltering adaptively shifts from high spatial frequencies to mediumspatial frequencies; and combining said video signal and said band-passfiltered video signal to produce an input video signal for saidhold-type display.

Said hold-type display may be understood as a non-stroboscopic display,i.e. images are shown on the display during a time period that is notnegligible with respect to the image period of the images. Examples forhold-type or non-stroboscopic display are for instance non-emissivedisplays, such as Liquid Crystal Displays (LCD), Plasma Panel Displays(PDP) and Thin Film Transistor (TFT) displays, which may for instanceconsist of a display panel having a row and column array of pictureelements (pixels) for modulating light, means for illuminating thedisplay panel from the from or back side, and drive means for drivingthe pixels in accordance with an applied input video signal. Furtherexamples of hold-type displays are emissive displays, such as OrganicLight Emitting Diode (O-LED) displays or Polymer Light Emitting Diodes(Poly-LED) displays, which may for instance consist of a display panelhaving a row and column array of pixels (LEDs) and drive means fordriving the pixels (LEDs) in accordance with an applied input videosignal. Therein, the pixels (LEDs) emit and modulate light by themselveswithout requiring illumination from the front or back side.

On said hold-type displays, images of a video signal are displayed,wherein said video signal is composed of a sequence of images andwherein said images are represented by image samples, for instancepicture elements (pixels). The images of said video signal that containscomponents or objects moving from one image to the next suffer frommotion blur when being viewed by a viewer, wherein said motion blur maybe described by a spatial frequency domain low-pass filtering of saidimages.

Motion vectors of said moving components in said images of said videosignal are estimated, for instance by means of a block-matchingalgorithm, that determines the displacement of components from one imageto the next. Motion vector then may be associated with said movingcomponents or with the samples or pixels of said moving components.

Said video signal is band-pass filtered in the spatial frequency domain,and subsequently said band-pass filtered video signal and said videosignal are combined, for instance added, to produce an input videosignal for said hold-type display. Different band-pass filtering may beapplied to different components or pixels of said images of said videosignal.

Said band-pass filtering is represented by a band-pass filter that has atransfer function in the spatial frequency domain with a pass-bandsection where the transfer function is non-zero and stop-band sectionsat the left and the right of said pass-band where the transfer functionis substantially zero.

Said band-pass filtering at least partially depends on said estimatedmotion vectors, for instance, said band-pass filtering may only beperformed in the direction of said estimated motion vectors. Withincreasing length of the estimated motion vectors (i.e. increasing speedof moving components in said images of said video signal), the pass-bandof said band-pass filter moves from higher spatial frequencies towardsmedium spatial frequencies, wherein this movement is adaptive withrespect to the length of the estimated motion vectors.

The combination of the band-pass filtered video signal and the originalvideo signal can be considered as a speed-dependent medium-frequencyenhancement (or boosting) filter structure, which limits the enhancementof components of the video signal to a medium spatial frequency rangeand which adaptively moves this frequency range from higher spatialfrequencies towards lower spatial frequencies when the amount of motionin the images of the video signal increases.

The present invention sets out from a first observation that, for highspeeds, the spatial frequency low-pass filter that causes the blurringhas a considerable attenuation at already very low spatial frequencies.A second observation is that the human visual system is more sensitiveto the lower spatial frequencies, and that the higher frequenciesgenerally have a lower signal-to-noise ratio. Finally, according to athird observation, it is noticed by the present invention that in commonvideo material, moving objects will not contain the highest frequenciesdue to the limitations of the camera (camera blur). For this reason,viewers are used to losing some detail at high speed, although not tothe extent (up to lower spatial frequencies) that is caused by LCDpanels.

In contrast to prior art techniques, wherein always high frequencyboosting is performed and wherein only the spatial frequency whereboosting starts is lowered with increasing motion, according to thepresent invention, priority is thus given to the compensation of thelowest frequencies that are affected by blurring, i.e. the mediumspatial frequencies, and the highest spatial frequencies are basicallyleft unchanged. This leads to a considerate improvement of motion blurreduction in video signals as compared to the prior art techniques.

According to a preferred embodiment of the present invention, saidband-pass filtering comprises low-pass filtering and anti-blur filteringin cascaded form. Said anti-blur filtering may for instance berepresented by a high-pass filter that is at least partially adapted tothe display characteristics of said display, and said low-pass filteringand subsequent-high-pass filtering then may result in a band-passfiltering. Said shift of said pass-band of said band-pass filtering mayfor instance be accomplished by shifting the lower edge of the pass-bandof the high-pass filter towards lower frequencies with increasing speed.

According to a preferred embodiment of the present invention, saidanti-blur filtering is performed with an anti-blur filter thatapproximates an inverted low-pass filter. Said low-pass filter may forinstance cause blurring and may depend on the length of the motionvectors (i.e. the speed of moving components in said images), so that tocompensate for the blurring, the inverse of said low-pass filter has tobe applied to said video signal, and wherein said inverse then alsodepends on the length of said motion vectors.

According to a preferred embodiment of the present invention, saidanti-blur filtering is performed with an anti-blur filter, and whereinsaid anti-blur filter is a one-dimensional filter with fixed filtercoefficients and a variable tap spacing that depends on said length ofsaid estimated motion vectors. Said anti-blur filter may for instance beapplied along the direction of said estimated motion vectors. By varyingsaid tap spacing, the spatial frequency transfer function of saidanti-blur filter may be changed, for instance, with increased tapspacing, a pass-band of said anti-blur filter may shift towards lowerfrequencies.

According to a preferred embodiment of the present invention, saidanti-blur filtering is performed in the direction of said estimatedmotion vectors. This is particularly advantageous if motion blur onlyoccurs in the direction of the motion vectors, so that, when alsofiltering only towards the direction of the motion vectors to reducemotion blur, only a minimum of noise enhancement occurs.

According to a preferred embodiment of the present invention, saidlow-pass filtering is performed in the direction of said estimatedmotion vectors. To reduce the number of pixels involved in the filteringprocess, and thus to reduce the computational complexity, it may beadvantageous to perform the low-pass filtering only in the direction ofthe estimated motion vectors.

According to a preferred embodiment of the present invention, saidlow-pass filtering is performed both in a direction perpendicular and ina direction parallel to the direction of said estimated motion vectors.Performing the low-pass filtering also in a direction perpendicular tothe direction of the estimated motion vectors may contribute to averageout noise contained in said samples of said images of said video signal.

According to a preferred embodiment of the present invention, saidlow-pass filtering is at least partially implemented by an interpolationof samples of said images of said video signal. Said interpolation mayfor instance contain averaging over several pixels, wherein saidaveraging can be considered as low-pass filtering.

According to a preferred embodiment of the present invention, saidband-pass filtering of said video signal comprises interpolating samplesof said images of said video signal to obtain interpolated samples,multiplying said interpolated samples with respective anti-blur filtercoefficients, and summing the products to obtain samples of images ofsaid band-pass filtered video signal. Said interpolation may forinstance be a 2D interpolation of samples to special positions, forinstance to the positions of the taps of a 1D or 2D anti-blur filter.Said interpolation may for instance be based on polynomial, rational, ortrigonometrical interpolation, or on any other interpolation technique.

According to a preferred embodiment of the present invention, saidanti-blur filter is a 1D anti-blur filter that is rotated according tothe direction of said estimated motion vectors, and wherein said samplesof said images of said video signals are interpolated to the positionsof the taps of said rotated 1D anti-blur filter.

According to a preferred embodiment of the present invention, saidanti-blur filter coefficients are independent of said estimated motionvectors. Said filter coefficients may for instance be pre-defined filtercoefficients that are optimized with respect to the displaycharacteristics of said hold-type display.

According to a preferred embodiment of the present invention, thespacing of said anti-blur filter coefficients depends on the length ofsaid estimated motion vectors. Said spacing, i.e. the spatial distancebetween the taps of said anti-blur filter, may increase with increasinglength of said estimated motion vectors.

According to a preferred embodiment of the present invention, saidsamples of said images of said video signal that are interpolated arelocated close to lines that interconnect the filter taps of said rotatedanti-blur filter.

According to a preferred embodiment of the present invention, saidsamples of said images of said video signal that are interpolated arelocated in a region that perpendicularly extends to both sides from saidlines that interconnect the filter taps of said rotated anti-blurfilter. Said interpolation then contains an additional averaging ofsamples perpendicular to the direction in which anti-blur filtering isapplied, and thus perpendicular to the direction of the estimated motionvectors. This may contribute to average out noise that is contained insaid samples.

According to a preferred embodiment of the present invention, saidinterpolation comprises an at least partial averaging of said samples ofsaid images of said video signal. Said averaging may contribute toaverage out noise and/or to perform an additional low-pass filtering ofsaid video signal.

According to a preferred embodiment of the present invention, saidband-pass filtering of said video signal comprises determining 2Dband-pass filters from a pre-defined set of 2D band-pass filters independence on said estimated motion vectors and filtering said videosignal with said selected 2D band-pass filters. Said pre-defined set of2D band-pass filters may for instance comprise pre-computed 2D band-passfilters for a plurality of possible lengths and directions of motionvectors in a tabular structure, so that a 2D band-pass filter may bechosen from said pre-defined set by selecting the pre-computed 2Dband-pass filter that is associated with the length and direction of amotion vector that is closest to the length and direction of saidestimated motion vector.

According to a preferred embodiment of the present invention, saiddetermining of said 2D band-pass filters comprises interpolating 2Dband-pass filters from 2D band-pass filters of said pre-defined set of2D band-pass filters. Said 2D band-pass filter may also be determinedfrom said pre-defined set of 2D band-pass filters by interpolating twoor more of the 2D band-pass filters contained in said set, depending onthe relation between the length and direction of the estimated motionvector and the length and direction of the motion vectors for which the2D band-pass filters in said pre-defined set of band-pass filters werecomputed. Said interpolating may contribute to reducing the requiredsize of said pre-defined set of 2D band-pass filters.

According to a preferred embodiment of the present invention, saidband-pass filtered video signal is further subject to noise suppressionprocessing before being combined with said video signal. Said noisesuppression processing may for instance suppress noise by discarding thelow-amplitude high spatial frequencies by coring, and/or by filteringsaid band-pass filtered signal with a non-linear order-statisticalfilter. Then frequency enhancement is only performed in regions wherethere is sufficient signal, as these are also the regions where motionblur is most objectionable.

A computer program is further proposed with instructions operable tocause a processor to perform the above-mentioned method steps. Saidcomputer program may for instance be processed by a Central ProcessingUnit (CPU) or any other processor integrated in a device that is relatedto the displaying of said images of said video signal, for instance adisplay, a television, or a monitor.

A computer program product is further proposed comprising a computerprogram with instructions operable to cause a processor to perform anyof the above-mentioned method steps. Said computer program product mayfor instance be a removable storage medium such as a disc, a memorystick, a memory card, a CD-ROM, DVD or any other storage medium.

A device for reducing motion blur of images of a video signal shown on ahold-type display is further proposed, said device comprising meansarranged for estimating motion vectors of moving components in saidimages of said video signal, means arranged for band-pass filtering saidvideo signal with respect to a spatial frequency domain, wherein saidband-pass filtering at least partially depends on said estimated motionvectors, and wherein with increasing length of said estimated motionvectors, the pass-band of said band-pass filtering adaptively shiftsfrom high spatial frequencies to medium spatial frequencies, and meansfor combining said video signal and said band-pass filtered video signalto produce an input video signal for said hold-type display.

Said device may for instance be realized as a separate unit processingthe video signals prior to sending them to a display. Said device mayalso be integrated into a display, or into a device that houses adisplay, as for instance a television, a monitor, a system operating ahead-mounted display, or a mobile multimedia device such as a mobilephone or a PDA.

These and other aspects of the invention will be apparent from andelucidated with reference to the embodiments described hereinafter.

BRIEF DESCRIPTION OF THE FIGURES

In the Figures show:

FIG. 1: A schematic illustration of the display chain comprising a stilloriginal image, a sampled image and a displayed image according to theprior art;

FIG. 2: spatio-temporal frequency spectra (as a function of normalizedtemporal frequency f_(t)Δt and normalized spatial frequency f_(x)Δx) oforiginal image I_(c), sampled image I_(s), displayed image I_(d) andperceived image (after eye low-pass) I_(p) corresponding to the samplingand displaying of an image on an impulse-type display according to theprior art;

FIG. 3: spatio-temporal frequency spectra of sampled image I_(s),aperture function A (with color code white representing low amplitudesand color code black representing high amplitudes), displayed imageI_(d) and perceived image (after eye low-pass) I_(p) corresponding tothe sampling and displaying of an image on a hold-type display accordingto the prior art;

FIG. 4: spatio-temporal frequency spectra of still original image I_(c),moving original image I_(m) and sampled original image I_(s) accordingto the prior art;

FIG. 5: a schematic illustration of the display chain from a movingoriginal image to a finally perceived image according to the prior art;

FIG. 6: spatio-temporal frequency spectra of displayed image I_(d),image after eye tracking I_(e) and image after eye low-pass I_(p) for animpulse-type display according to the prior art, complementing FIG. 4;

FIG. 7: spatio-temporal frequency spectra of aperture function A,displayed image I_(d), image after eye tracking I_(e) and image aftereye low-pass I_(p) for a hold-type display according to the prior art,complementing FIG. 4;

FIG. 8: schematic amplitude response of the spatial filter H^(f)({rightarrow over (f)}_(x)) due to temporal display aperture and eye trackingas a function of spatial frequency and speed, with speed measured inpixels per frame, f_(x) expressed in cycles per pixels, and T_(h)=1frame);

FIG. 9: a schematic illustration of the display chain from video signalto perceived image with a pre-compensation filter according to the priorart;

FIG. 10: the transfer function of the display+eye filter H^(f)({rightarrow over (f)}_(x)), the corresponding inverse filter H_(inv)^(f)({right arrow over (f)}_(x)), and an approximation thereof as afunction of the spatial frequency according to the prior art, for aspeed of three pixels per frame;

FIG. 11: an exemplary speed-dependent medium frequency boosting filterstructure for reducing motion blur according to the present invention;

FIG. 12: a schematic illustration of the rotation and thespeed-dependent tap spacing of the 1D anti-blur filter contained in thefilter structure of FIG. 11 according to the present invention;

FIG. 13: exemplary transfer functions of the filter structure accordingto FIG. 11 (solid lines) and of the ideal inverse filter (dashed lines)as a function of the normalized spatial frequency for different speedsaccording to the present invention;

FIG. 14: a schematic illustration of the samples of the video samplinggrid involved in the interpolation of samples to the 1D anti-blur filtertap positions according to the present invention;

FIG. 15 a: a schematic illustration of the samples of the video samplinggrid involved in the interpolation of samples to the 1D anti-blur filtertap positions with increased averaging according to the presentinvention;

FIG. 15 b: a schematic illustration of the samples of the video samplinggrid involved in the interpolation of samples to the 1D anti-blur filtertap positions with increased number of filter taps according to thepresent invention;

FIG. 16: exemplary transfer functions of a medium frequency boostingfilter structure according to FIG. 11 (solid lines) and of the idealinverse filter (dashed lines) as a function of the normalized spatialfrequency for different speeds according to the present invention;

FIG. 17: a schematic amplitude response of the combination of the filterstructure according to FIG. 16 and the display+eye combination as afunction of motion (in pixels per frame) and normalized spatialfrequency; and

FIG. 18: a schematic illustration of the samples of the video samplinggrid involved in the interpolation of samples to the 1D anti-blur filtertap positions under additional usage of samples positioned farther apartfrom the line defined by the filter taps according to the presentinvention;

DETAILED DESCRIPTION OF THE INVENTION

The present invention sets out from the observation that the display+eyefilter H^(f)({right arrow over (f)}_(x)) of Eq. (11), as illustrated inFIG. 8, at high speeds has a considerable attenuation at already verylow spatial frequencies. Furthermore, it is recognized that the humanvisual system is more sensitive to the lower spatial frequencies, andthat the higher frequencies generally have a lower signal-to-noiseratio. Furthermore, the present invention recognized that in commonvideo material, moving objects will not contain the highest frequenciesdue to the limitations of the camera (camera blur). For this reason,viewers are used to losing some detail at high speed, although not tothe extent (up to lower spatial frequencies) that is caused by LCDpanels.

According to the present invention, in case of high speeds, it is thusproposed to give priority to the compensation of the lowest affectedfrequencies, and to leave the highest frequencies basically unchanged.This transforms the prior art high-frequency boosting filter, whichserves as an approximation of the inverse filter of Eq. (12), cf. FIG.9, into a medium-frequency boosting filter, which limits theamplification of the higher frequencies at high speeds, and onlycompensates the lowest frequencies.

FIG. 11 shows a corresponding embodiment of a filter structure 11 of thepresent invention. Pixels of images of a video signal are fed into amotion estimator instance 1102, in which both the length and thedirection of motion vectors associated with moving objects in saidimages of said video signal are estimated, for instance via a 3Drecursive block matching algorithm or similar techniques. Said pixels ofimages of a video signal are also fed into a 2D interpolation instance1100. This interpolation instance 1100 uses a 2D neighborhood around acurrent pixel taken from an image of said video signal, and, based onthe estimated direction of the motion vector that is associated withsaid current pixel, returns a 1D series (line) of samples to the 1Danti-blur filter 1101. The coefficients of said 1D anti-blur filter maybe fixed, they may for instance be pre-determined and adapted to thecharacteristics of the display.

The samples resulting from the interpolation correspond to the taps ofthe 1D anti-blur filter 1101. These samples are subsequently multipliedwith the 1D anti-blur filter tap coefficients and accumulated, to resultin a single “correction” value for the current pixel. This operation isnot a conventional convolution filtering, since the applied line ofsamples can totally change from one pixel to the next, if the motionvector changes. Said 2D interpolation and said subsequent multiplicationof the interpolated pixels with the filter tap coefficients can beconsidered as an orientation of the 1D anti-blur filter kernel along themotion vectors by rotating the 1D filter kernel, which makes thefiltering actually a 2D filtering. The interpolation accounts for thefact that the rotated 1D anti-blur filter taps generally do not coincidewith sample (pixel) positions in the image. This interpolation may forinstance be a bi-linear interpolation or any other type ofinterpolation.

The positions of these interpolated pixels (or the corresponding 1Danti-blur filter taps) vary not only with the direction of the motionvector, but also lie at a larger distance from the central tap forhigher speeds. This shifts the response of the 1D anti-blur filtertowards lower frequencies for increasing length of the motion vectors.This is symbolically illustrated in FIG. 11 by inputting the length ofthe motion vectors (or speed of components in the images of the videosignal) as estimated by the motion estimation instance 1102 into the 1Danti-blur filter 1101. It is readily seen that, in particular when thefilter tap coefficients of the 1D anti-blur filter 1101 are fixed, thespacing of the 1D anti-blur filter taps can also be adjusted during the2D interpolation in interpolation instance 1102. Then the estimatedlength and direction of the motion vectors is fed from said motionestimation instance 1102 to said 2D interpolation instance 1100.

The filtered pixels as output by the 1D anti-blur filter 1101 may thenbe fed into an optional noise reduction instance 1103. This noisereduction instance may for instance perform “coring” on said pixels,i.e. noise is suppressed by discarding the low-amplitude highfrequencies, and/or filter said pixels with a non-linearorder-statistical filter. These techniques will contribute to applyingthe frequency enhancement only in regions where there is sufficientsignal, as these are also the regions where motion blur is mostobjectionable.

The filtered and possibly noise-reduced pixels are then added to thepixels of the original video signal by means of an adder 1104, and thenare fed to a hold-type display.

From the structure of the filter 11, it is readily seen that the displayis fed with the sum of the original video signal and a filtered versionof said original video signal, wherein said filtering is specific forpixels or groups of pixels within the images of said video signal andonly takes place along the estimated motion vectors. Furthermore, aswill be explained in the following, said 2D interpolation and 1Dfiltering implement a band-pass filtering that only takes place in aband-limited frequency range that depends on the estimated length of themotion vectors, wherein said frequency range is shifted from highfrequencies to medium frequencies with increasing motion in said videosignal. Optionally the enhancement of the frequency components withinthe band-limited frequency range can be suppressed by said noisereduction instance 1103. The complete system 11 thus represents a mediumfrequency boosting filter, wherein the boosted frequency range movesfrom higher to lower frequencies for increasing motion in the videosignal.

FIG. 12 shows a portion of the video sampling grid 12 as dark boxes, anddifferent rotations and tap spacings of an exemplary three-tap 1Danti-blur filter as gray boxes, wherein the three taps areinterconnected with dashed lines that indicate the direction of thefiltering. It is readily seen from FIG. 12 that the pixel positions ofthe video sampling grid do not necessarily coincide with the positionsof the 1D anti-blur filter that is rotated according to the direction ofthe estimated motion vectors. It can also clearly be seen that theposition of the center tap of the three-tap 1D anti-blur filter remainsconstant when the tap spacing increases due to increased length of themotion vectors (or, speed of components in the images).

FIG. 13 shows the transfer function of the filter structure 11 (composedof 2D-interpolation, rotated 1D anti-blur filter and adder) as afunction of the normalized spatial frequency in solid lines (1201 a . .. 1204 a), and also the transfer function of the ideal inverse filter indashed lines (1201 b . . . 1204 b), wherein both the transfer functionof the filter structure 11 and the ideal inverse filter are given fordifferent speeds, which decreases from filters 1201 a to 1204 a and 1201b to 1204 b, respectively. It is readily seen from the ideal inversefilters, that with increasing speed, the spatial frequency where theenhancement of the ideal inverse filter starts is moving towards smallerspatial frequencies. For fixed speeds, the transfer functions of thefilter structure 11 represent a good approximation of the correspondingideal inverse filter for small spatial frequencies. However, when thetaps of the 1D anti-blur filter of the filter structure 11 are simplyshifted away from the central tap at increasing speed, as shown in FIG.12, the transfer function becomes periodic, and high frequencies canstill pass the filter. This happens when input samples are ‘skipped’during the filtering.

FIG. 14 shows which samples (the black boxes) on the video sampling grid14 (the white boxes) are used to calculate each interpolated sample (fora bi-linear interpolation). The skipping of samples between the filtertaps, in particular between the center filter tap and the respectiveleft and right interpolated outer filter tap is obvious in this example.

To solve this problem, the present invention proposes to change theresponse of the filter structure 11, to actually suppress the veryhighest frequencies for high speeds. This is achieved by using aninterpolation method that suppresses these frequencies before the tapmultiplications, i.e. that uses (averages) more original samples tocompute an interpolated sample.

FIG. 15 a illustrates this principle. In contrast to FIG. 14, now morethan four samples are used for the interpolation of the samplesassociated with the leftmost and rightmost filter tap.

An alternative approach to suppress the periodicity of the 1D anti-blurfilter for higher speeds is to first interpolate more samples, and thento use a filter with more taps that suppresses the high frequencies.This approach is depicted in FIG. 15 b, where the number of taps hasbeen increased from 3 to 5.

The suppression of high frequencies at high speeds can also be achievedby cascading the 1D anti-blur filter with a speed-dependent low-passfilter, or by storing a number of (1D) filters for various speeds. Theresulting transfer functions 1601 a . . . 1604 a of the filter structurefor different speeds as a function of the normalized spatial frequency,and the corresponding ideal inverse filters 1601 b . . . 1604 b areshown in FIG. 16, wherein speed decreases from filter 1601 to 1604,respectively.

From FIG. 16, it can be readily seen that the filter structure 11 ofFIG. 11 now can be considered to consist of an all-pass filter (thedirect feed of the original video signal to the adder 1104) and aband-pass filter (the combination of 2D interpolation and 1D anti-blurfilter) that are added to obtain the transfer functions of FIG. 16. Bysubtracting “1” from the transfer functions 1601 a . . . 1604 a of thefilter structure, thus the transfer function of the combination of 2Dinterpolation and 1D anti-blur filter is obtained, which exhibits aband-pass characteristic. The pass-band of this band-pass characteristicshifts from high spatial frequencies to medium spatial frequencies withincreasing speed, wherein this shift is performed adaptively in responseto the estimated length of the motion vectors, which affects the tapspacing of the 1D anti-blur filter. The rotation of the 1D anti-blurfilter response as performed by the 2D interpolation ensures that theband-pass filtering is only applied along the direction of the motionvectors.

FIG. 17 schematically depicts the amplitude of the combination of thefilter structure 11 and the display+eye combination as a function ofmotion (in pixels per frame) and normalized spatial frequency. Therein,the white area represents amplitudes between 1 and 0.5, and the shadedregion represent amplitudes between 0.5 and 0). From the white area inFIG. 17 b, it can clearly be seen that with increasing speed, theenhancement of spectrum components at large spatial frequencies, whichis performed by the filter structure according to FIG. 11, issignificantly reduced in favor of the spectrum components at medium andsmall frequencies.

To further reduce the impact of noise on the filtered video signal, alsoa low-pass filtering perpendicular to the motion direction can bebeneficial, which can be achieved by also using samples further awayfrom the line of the motion in the 2D interpolation.

This concept is illustrated in FIG. 18, where the white boxes denote thevideo sampling grid 18, the gray boxes denote the taps of the rotated 1Dfive-tap filter and the black boxes denote the samples used for theinterpolation of samples towards the filter tap positions. In contrastto FIG. 15 b, it is noted that the region that perpendicularly extendsfrom the line defined by the filter taps and that contains the samplesthat are used for the interpolation is wider than in FIG. 15 b, thustaking into account more samples in perpendicular direction to thedirection of the motion vectors to increase the averaging effect andthus to suppress noise.

The resulting filter thus has a low-pass behavior perpendicular to themotion, and a band-pass behavior along the motion.

Finally, alternative to implementing the filters as a directionaldependent interpolation followed by a (1D) filtering, the filters can becalculated for a number of angles and speeds (a number of motionvectors), and stored in a table. The filtering then comes down toapplying a different 2D filter for each pixel, where the coefficients ofthis filter are according to the principles mentioned in this part ofthe specification. The number of stored filters can be limited, when‘intermediate’ filters are calculated (interpolated) based on the storedones.

To evaluate the performance of the present invention, the filterstructure 11 according to FIGS. 11 and 17 was tested on an LCD-TVsimulation setup, which consists of a PC-based video streamer that canplay back stored sequences in real time, a DVI to LVDS panel interfaceboard, and a 30 inch LCD-TV panel (1280×768@60 Hz, without additionalprocessing). Although the panel had a listed response time of 12 ms, ameasurement was performed of the response times for each gray leveltransition, and an average response time of 20 ms was found. To furtherincrease the response speed, (a moderate amount of) overdrive was usedto get the response time to within one frame time.

By means of comparison with a CRT display, it could be observed thatthere was not visibly more motion blur on the LCD than on the CRT. Onlyfor very critical (graphics-like) sequences, motion blur was stillvisible.

The invention has been described above by means of preferredembodiments. It should be noted that there are alternative ways andvariations which are obvious to a skilled person in the art and can beimplemented without deviating from the scope and spirit of the appendedclaims.

1. A method for reducing motion blur of images of a video signal shownon a hold-type display, comprising: estimating motion vectors of movingcomponents in said images of said video signal; band-pass filtering saidvideo signal with respect to a spatial frequency domain, wherein saidband-pass filtering at least partially depends on said estimated motionvectors, and wherein with increasing length of said estimated motionvectors, the passband of said band-pass filtering adaptively shifts fromhigh spatial frequencies to medium spatial frequencies, whereinband-pass filtering includes anti-blur filtering performed with ananti-blur filter that comprises a one-dimensional filter with a variabletap spacing that depends on said length of said estimated motionvectors; and combining said video signal and said band-pass filteredvideo signal to produce an input video signal for said hold-typedisplay.
 2. The method according to claim 1, wherein said band-passfiltering comprises low-pass filtering and anti-blur filtering incascaded form.
 3. The method according to claim 2, wherein saidanti-blur filtering is performed with an anti-blur filter thatapproximates an inverted low-pass filter.
 4. The method according toclaim 2, wherein said anti-blur filter is a one-dimensional filter withfixed filter coefficients and a variable tap spacing that depends onsaid length of said estimated motion vectors.
 5. The method according toclaim 2, wherein said anti-blur filtering is performed in the directionof said estimated motion vectors.
 6. The method according to claim 2,wherein said low-pass filtering is performed in the direction of saidestimated motion vectors.
 7. The method according to claim 2, whereinsaid low-pass filtering is performed both in a direction perpendicularand in a direction parallel to a direction of said estimated motionvectors.
 8. The method according to claim 2, wherein said low-passfiltering is at least partially implemented by an interpolation ofsamples of said images of said video signal.
 9. The method according toclaim 1, wherein said band-pass filtering of said video signalcomprises: interpolating samples of said images of said video signal toobtain interpolated samples; and multiplying said interpolated sampleswith respective anti-blur filter coefficients and summing thecorresponding products to obtain samples of images of said band-passfiltered video signal.
 10. The method according to claim 9, wherein saidanti-blur filter is a 1D anti-blur filter that is rotated according to adirection of said estimated motion vectors, and wherein said samples ofsaid images of said video signals are interpolated to positions of tapsof said rotated anti-blur filter.
 11. The method according to claim 9,wherein said anti-blur filter coefficients are independent of saidestimated motion vectors.
 12. The method according to claim 9, wherein aspacing of said anti-blur filter coefficients depends on the length ofsaid estimated motion vectors.
 13. The method according to claim 10,wherein said samples of said images of said video signal that areinterpolated are located close to lines that interconnect the filtertaps of said rotated anti-blur filter.
 14. The method according to claim10, wherein said samples of said images of said video signal that areinterpolated are located in a region that perpendicularly extends toboth sides from lines that interconnect the filter taps of said rotatedanti-blur filter.
 15. The method according to claim 9, wherein saidinterpolation comprises an at least partial averaging of said samples ofsaid images of said video signal.
 16. The method according to claim 1,wherein said band-pass filtering of said video signal further comprises:determining 2D band-pass filters from a pre-defined set of 2D band-passfilters in dependence on said estimated motion vectors; and filteringsaid video signal with said determined 2D band-pass filters.
 17. Themethod according to claim 16, wherein said determining of said 2Dband-pass filters comprises interpolating 2D band-pass filters from 2Dband-pass filters of said pre-defined set of 2D band-pass filters. 18.The method according to claim 1, wherein said band-pass filtered videosignal is further subject to noise suppression processing before beingcombined with said video signal.
 19. A computer-readable mediumembodying a computer program with instructions operable to cause aprocessor to perform the method of claim
 1. 20. A computer-readablemedium embodying a computer program with instructions operable to causea processor to perform the method of claim
 9. 21. A device for reducingmotion blur of images of a video signal shown on a hold-type display,comprising: means arranged for estimating motion vectors of movingcomponents in said images of said video signal; means arranged forband-pass filtering said video signal with respect to a spatialfrequency domain, wherein said band-pass filtering at least partiallydepends on said estimated motion vectors, and wherein with increasinglength of said estimated motion vectors, the pass-band of said band-passfiltering adaptively shifts from high spatial frequencies to mediumspatial frequencies, wherein band-pass filtering includes anti-blurfiltering performed with an anti-blur filter that comprises aone-dimensional filter with a variable tap spacing that depends on saidlength of said estimated motion vectors; and means for combining saidvideo signal and said band-pass filtered video signal to produce aninput video signal for said hold-type display.